Covid Report for Family

Background

Notes and format last updated May 7, 2020

Starting on the May 7th update, the NY Times began including probable covid cases/deaths along with confirmed. This mostly affects death counts – for certain geographies that include probable COVID deaths in addition to confirmed, these are now added to the totals. For the time being, they were all added to the May 6th totals, causing a big spike at the U.S. level. Over time, NY Times will revise their historical counts and distribute these added deaths when they actually occurred, so the spike should fade.

• This page shows COVID data broken down into regions that affect our family. It pulls from publicly available raw data from the NY Times, which is reported daily. It’s on a one-day lag, so when you see this report, the most recent day included will be that reported the day prior.
• The table of contents above summarizes the major sections and can be used to jump to those sections.
• Each major section is then divided into tabs to allow you to more easily shuffle between geographies and metrics.
  • If you open on your phone, I don’t believe the tabs will work, so you’ll just see the page as one long, continuous document.
• More detailed descriptions and context can be found in each section.

Growth rates

Heat maps

• The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
• The first plot compares growth rate for total cases; the second, growth rate for total deaths.
• The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
• The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
  • You can use the plots to track each geography over time and to compare the geographies to one another.
  • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
  • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
  • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

• This section charts the growth rate of both total and new deaths for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total deaths and new deaths.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
• Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
  • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
  • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

• This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
• For each metric, in addition to the tables, the trends for the top states are plotted over time.
  • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)

Ranking	State	Cases Per Million
1	North Dakota	131,775
2	South Dakota	128,398
3	Rhode Island	120,941
4	Utah	116,922
5	Arizona	113,543
6	Tennessee	112,628
7	Oklahoma	108,415
8	Iowa	107,659
9	Arkansas	107,633
10	Wisconsin	106,768
11	Nebraska	105,098
12	Kansas	102,597
13	South Carolina	102,135
14	Alabama	101,937
15	Mississippi	99,988
16	Indiana	99,595
17	Idaho	96,812
18	Nevada	96,188
19	Illinois	94,837
20	Wyoming	94,623
21	Montana	94,470
22	Georgia	94,020
23	Louisiana	93,311
24	Texas	92,973
25	Kentucky	92,710
26	New Jersey	91,487
27	California	91,091
28	Delaware	90,734
29	Florida	90,558
30	New Mexico	89,145
31	New York	87,125
32	Minnesota	86,899
33	Massachusetts	85,796
34	Missouri	84,791
35	Ohio	83,707
36	North Carolina	83,575
37	Alaska	80,473
38	Connecticut	80,030
39	Colorado	76,010
40	Pennsylvania	74,474
41	West Virginia	74,460
42	Virginia	68,619
43	Michigan	65,684
44	Maryland	64,095
45	District of Columbia	58,688
46	New Hampshire	56,527
47	Washington	45,619
48	Puerto Rico	42,406
49	Oregon	37,306
50	Maine	34,067
51	Vermont	25,774
52	Hawaii	19,649

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Cases Per Million
1	New York	410
2	New Jersey	373
3	South Carolina	278
4	Massachusetts	244
5	Delaware	243
6	Florida	229
7	Arizona	228
8	Vermont	212
9	Oklahoma	198
10	South Dakota	197
11	District of Columbia	191
12	Georgia	183
13	Pennsylvania	181
14	Kentucky	169
15	New Hampshire	167
16	Virginia	167
17	Tennessee	160
18	Mississippi	159
19	Utah	159
20	Minnesota	155
21	West Virginia	142
22	Indiana	140
23	Maine	140
24	Maryland	140
25	Texas	138
26	Nebraska	134
27	Illinois	132
28	Colorado	131
29	Rhode Island	123
30	North Carolina	122
31	New Mexico	121
32	Alabama	118
33	Nevada	118
34	Arkansas	117
35	Iowa	114
36	Michigan	113
37	Ohio	113
38	Montana	102
39	California	101
40	Puerto Rico	99
41	Wisconsin	98
42	Louisiana	90
43	North Dakota	90
44	Kansas	78
45	Connecticut	77
46	Missouri	70
47	Alaska	67
48	Washington	59
49	Idaho	54
50	Hawaii	51
51	Oregon	50
52	Wyoming	45

Total deaths

Table of total deaths per million residents (all 50 states)

Ranking	State	Deaths Per Million
1	New Jersey	2,654
2	New York	2,460
3	Rhode Island	2,398
4	Massachusetts	2,381
5	Mississippi	2,287
6	Arizona	2,243
7	Connecticut	2,160
8	South Dakota	2,147
9	Louisiana	2,096
10	Alabama	2,069
11	North Dakota	1,940
12	Pennsylvania	1,905
13	Indiana	1,891
14	Illinois	1,816
15	New Mexico	1,816
16	Arkansas	1,762
17	Iowa	1,761
18	South Carolina	1,700
19	Tennessee	1,676
20	Michigan	1,666
21	Kansas	1,651
22	Nevada	1,635
23	Georgia	1,633
24	Texas	1,567
25	Delaware	1,512
26	Ohio	1,497
27	Florida	1,475
28	District of Columbia	1,459
29	Missouri	1,402
30	California	1,372
31	Maryland	1,315
32	West Virginia	1,297
33	Montana	1,293
34	Wisconsin	1,221
35	Wyoming	1,178
36	Minnesota	1,173
37	Nebraska	1,149
38	Oklahoma	1,145
39	Virginia	1,124
40	Kentucky	1,110
41	North Carolina	1,098
42	Colorado	1,054
43	Idaho	1,053
44	New Hampshire	870
45	Washington	670
46	Puerto Rico	646
47	Utah	616
48	Oregon	546
49	Maine	525
50	Alaska	399
51	Vermont	333
52	Hawaii	312

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)

Ranking	State	New Deaths Per Million
1	Ohio	21
2	Delaware	9
3	Virginia	9
4	Arizona	6
5	California	6
6	South Carolina	6
7	Texas	6
8	Arkansas	5
9	Kentucky	5
10	Massachusetts	5
11	New Mexico	5
12	New York	5
13	Florida	4
14	Georgia	4
15	Louisiana	4
16	Mississippi	4
17	Alabama	3
18	Indiana	3
19	Nevada	3
20	New Jersey	3
21	Pennsylvania	3
22	District of Columbia	2
23	Illinois	2
24	Iowa	2
25	Michigan	2
26	Missouri	2
27	North Carolina	2
28	Tennessee	2
29	West Virginia	2
30	Connecticut	1
31	Maryland	1
32	Minnesota	1
33	Montana	1
34	Nebraska	1
35	New Hampshire	1
36	Oregon	1
37	Puerto Rico	1
38	South Dakota	1
39	Utah	1
40	Wisconsin	1
41	Alaska	0
42	Colorado	0
43	Hawaii	0
44	Idaho	0
45	Kansas	0
46	Maine	0
47	North Dakota	0
48	Oklahoma	0
49	Rhode Island	0
50	Vermont	0
51	Washington	0
52	Wyoming	0

Counties

• This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
  • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
• In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Cases Per Million	Raw Ranking	Percentile
Crowley	Colorado	342,023	1	99
Chattahoochee	Georgia	287,980	2	99
Bent	Colorado	265,555	3	99
Lincoln	Arkansas	242,475	4	99
Dewey	South Dakota	241,514	5	99
Davidson	Tennessee	130,140	231	92
Richland	South Carolina	100,893	1069	65
York	South Carolina	96,352	1265	59
Orange	California	82,714	1898	39
Pierce	Washington	43,136	2902	7

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Deaths Per Million	Raw Ranking	Percentile
Gove	Kansas	8,346	1	99
Jerauld	South Dakota	7,948	2	99
Galax city	Virginia	7,878	3	99
Foard	Texas	7,792	4	99
Emporia city	Virginia	7,669	5	99
Orange	California	1,331	1857	40
Davidson	Tennessee	1,259	1954	37
Richland	South Carolina	1,219	2021	35
York	South Carolina	1,210	2030	35
Pierce	Washington	622	2708	13

Our county percentiles over time

Raw counts

• This section shows the raw counts over time for the U.S., our states, and our counties for four categories:
  • Total confirmed cases: This is the cumulative total of cases reported.
  • New confirmed cases: This is the number of new cases reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new cases, to help better visualize the peak.
  • Total deaths: This is the cumulative total of deaths reported.
  • New deaths: This is the number of new deaths reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new deaths, to help better visualize the peak.

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons

• This section is a work in progress. It’s exploring what effect stay-at-home orders have on spread. It’s inherentely messy because some states have localized orders but not orders for their full state and because states implemented the orders at different times.
  • The first plot shows a rolling 3-day average of new cases per million residents, averaged across 2 groups of states – those with a state-wide stay-at-home order in effect and those without. The size of the dots reflect the number of states in each group for each given day (so the dots are getting bigger over time for the group with orders, as more states implement those orders).
    • So far, this view doesn’t show if these orders are “working” or not. Instead, the biggest takeaway from the current plot is that the states that implemented orders are reacting to having worse spread, which is why the case rate is so much higher at the start for them. As a state decides it has a problem and implements an order, it joins the grouping of states with orders and drives the rate up for that group.
    • Over time (if the policies work), what we’d expect is that the line for the group with orders flattens or declines in relation to the no-order group. It also may become moot if all states issue orders.
    • As states start rescending their orders, I’ll put them back into the no-order group, so the no-order group should beging to expand again.
  • The second plot tracks progress of states by the number of days since orders have been in effect. It includes only those states with orders and shows their average new case growth rate (a rolling 3-day average of daily growth rates) based on how long it’s been since the order went into effect. Again, the size of the dots show how many states are included in each point – i.e., as you go further right, the dots are smaller because less states are that far past their order.
    • I’m working on how to add a baseline to this chart to compare to states without orders, but that’s challenging because there’s no way to fully align timing.